
#for part in ensemble_train ensemble_validate test; do 
for part in train; do 
  CUDA_VISIBLE_DEVICES=1 python inference-pre-ensemble.py \
      --output_dir="/Youtube-8M/model_predictions_x32/${part}/distillation/distillchain_video_dcc" \
      --model_checkpoint_path="../model/distillation/distillchain_video_dcc/model.ckpt-19296" \
      --input_data_pattern="/Youtube-8M/data/video/${part}/*.tfrecord" \
      --frame_features=False \
      --feature_names="mean_rgb,mean_audio" \
      --feature_sizes="1024,128" \
      --distill_data_pattern="/Youtube-8M/model_predictions/${part}/distillation/ensemble_mean_model/*.tfrecord" \
      --distillation_features=True \
      --distillation_as_input=True \
      --model=DistillchainDeepCombineChainModel \
      --moe_num_mixtures=4 \
      --deep_chain_layers=4 \
      --deep_chain_relu_cells=256 \
      --batch_size=32 \
      --file_size=4096
done
